Quantitative Developer Intern: AI-Driven Trading & Research

Jain Global, LLC; New York (NY); On-site; USD 182,000 - 234,000; Full time

Job summary

Jain Global seeks a Quantitative Developer Intern to join its Technology and Research team in New York City. You'll work at the intersection of quantitative research, technology, and financial markets, developing trading systems and analytical frameworks.

Collaborate with portfolio managers, researchers, and technologists to turn data into insights and insights into execution, gaining hands-on experience in data analysis, model implementation, and AI-driven systematic investment strategies.

Qualifications

• Pursuing a Master’s or Ph.D. in Computational Finance, Mathematics, CS, or a related field.
• Strong Python or C++ programming and numerical computation.
• Solid statistics and ML tooling interest.

Responsibilities

• Design, develop, and optimize software tools for trading and research infrastructure.
• Apply computational and technical skills to problems at the intersection of trading and technology.
• Implement and evaluate ML tools to enhance trading models and workflows.
• Perform exploratory data analysis and statistical modeling on large datasets to inform strategies.
• Support automation of data workflows and real-time analytics for production systems.
• Backtest strategies, analyze performance, and deploy insights into live environments.
• Contribute to system performance, scalability, and reliability.

Skills

Python

C++

Statistics

Machine learning

Communication

Teamwork

Education

Master's or PhD in Computational Finance/Math/CS

Tools

Pandas

NumPy

Scikit-learn

Job description

Jain Global seeks a Quantitative Developer Intern to join its Technology and Research team in New York City. You'll work at the intersection of quantitative research, technology, and financial markets, developing trading systems and analytical frameworks.

Collaborate with portfolio managers, researchers, and technologists to turn data into insights and insights into execution, gaining hands-on experience in data analysis, model implementation, and AI-driven systematic investment strategies.